In recent years the Internet has grown so fast that E-businesses are becoming highly profitable. Internet database systems provide business information from which an unprecedented number of customers may access. With the drastic growth of Internet users, the demand for higher system throughput becomes urgent. Replicated database systems have attracted considerable attention due to their apparent advantages of improved data availability and system scalability. In a replicated database system, identical copies of data objects are kept in multiple geographically distributed sites to provide nearby customers with fast and easy accesses. The multiple copies of data objects also provide a much more reliable information service against system outages, which might otherwise cause severe losses in E-businesses, such as online stock trading systems. However, while the replication paradigm brings the benefit of quick response to read-only operations, it does cause new problems—the workload of updates in each site increases proportionally to the number of replicas of data objects. It has been discussed that the deadlock rate has a cubic growth versus the number of replicas. This implicates that two-phase locking, the most commonly used locking-based concurrency control method, cannot meet the increasing needs of high performance in today's Internet database systems such as online shopping systems, stock trading systems, etc.
The relative performance of three different approaches for concurrency control, i.e., blocking-based, immediate-restart, and optimistic, under a variety of modeling assumptions have been studied. In the blocking-based approach, transactions set read locks on objects that they read, then upgrade the read locks to write locks for the objects that they also write. When a lock request is denied, the requesting transaction is blocked. Wait-for-graph is used for deadlock detection. In the immediate-restart approach, transactions lock the objects in the same way as in the blocking-based approach, but they are aborted immediately when a lock request is denied. In the optimistic approach, transactions are allowed to be executed unhindered and are validated only after they have reached their commit points, but they are restarted if any object they read has been written by other committed transactions. The conclusion is that a concurrency control method that tends to conserve physical resources by blocking transactions, such as S2PL, out performs immediate-restart and optimistic methods for medium to high levels of resource utilization. In an environment of sufficient resources of CPUs and disks, an optimistic method is a better choice in terms both system throughput and transaction response time.
With the fast progress of technologies, the available resources may no longer be a bottleneck, e.g., CPU speed increases drastically and the costs of disks and CPUs are dropping quickly. Thus, optimistic approaches seem more promising than ever. It has been proposed that a hybrid two-phase concurrency control method be used wherein, in the first execution phase an optimistic concurrency control method is used, and in the restart phase a conservative 2PL is used. With such a method it was found that, statistically, transactions intend to access the same dataset as before, if they are restarted due to access conflicts. With the access invariance property, this method ensures, at most, one transaction re-execution. This eliminates the repeated restart problems in optimistic concurrency control methods and makes transaction response time more predictable.